wal2json VS flyctl

To illustrate the above, let’s look at an example, using wal2json for convenience. An update event looks something like this:

You could also use tools in conjunction with logical replication to stream changes, like debezium or wal2json.

I've done CDC before for mysql and postgres, in both cases, rolled my own 200~ loc python scripts. No experience with DMS. Debezium, as I understand, needs a kafka topic to stream to, so wasn't workable for us. Rolling our own proved to be fairly trivial. For postgres, there's wal2json https://github.com/eulerto/wal2json

I was researching for the whole day and found out https://github.com/eulerto/wal2json and postgres bult-in `pgoutput` plugin help me to catch the changes.

I don't think this is something for "rails" to do per se, and more the underlying DB. replication tools to capture a "change log". I have use postgres Write Ahead Logs (WAL) shipped to s3 in json format https://github.com/eulerto/wal2json

[0] https://supabase.com [1] https://github.com/supabase/realtime [2] https://github.com/eulerto/wal2json [3] https://github.com/supabase/walrus [4] https://gsd.di.uminho.pt/members/cbm/ps/delta-crdt-draft16ma... [5] https://supabase.com/blog/2022/04/01/supabase-realtime-with-... [6] https://fly.io [7] https://github.com/supabase/realtime/tree/multiplayer [8] https://github.com/supabase/supabase/tree/master/docker

wal2json Output Plugin that converts WAL output to JSON objects [Open Source] pg_recvlogical Postgres app that can consume update stream [Out-of-the-box with Postgres] decoderbufs Output Plugin that delivers data as protobuf [Open Source, Used in Debezium]

To begin visit fly.io to create an account. Next install flyctl a command line tool for creating and deploying fly apps. macOS

For frontend deployment, I used Netlify (for the generous free package) and the recommended fly.io for server + database (also cheap package).

Create an account on Fly.io.

You can learn more about fly.io and tigris, we will need to create an account on both platforms for this project regardless. Anyway with the theory out of the way let's get started in the next section as we create our accounts and start building the app.

Fly.io is a platform that helps you run your apps and databases closer to your users all around the world. It takes your app code, packages it up neatly, and puts it on virtual machines that can be quickly started or stopped. This makes your app faster for users and more reliable. Fly.io is easy to use, works well for small projects or personal apps. It's a great way to make sure your app runs smoothly for people no matter where they are.

In this post, we'll start from scratch, running FerretDB locally via Docker, trying out the connection with mongosh and the MongoDB Node.js client, and finally deploy FerretDB to Fly.io for a production ready set up.

2- fly.io

Fly is a cloud platform that focuses on global edge computing. Fly specializes in high-performance hosting and provides a global network of edge locations. Fly is known for its scalability and performance optimizations.

But videototextai.com is built using NextJS + Firebase auth + Firestore and a backend deployed at fly.io . Fly makes it really easy to deploy docker containers and that is IMO the fastest way to develop, you can setup a local setup

Alternatives explored: * northflank: While running the wrk test, requests were taking 3-7 seconds. Couldn't repeat Heroku's phenomenon of "400ms-800ms" during such a load test. * fly.io: Reliability: It’s Not Great * render.com: I remember the time when indiehackers.com was down because of an outage on Render, not sure if it's worth trusting.